The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

e2tree: Explainable Ensemble Trees

The Explainable Ensemble Trees 'e2tree' approach has been proposed by Aria et al. (2024) <doi:10.1007/s00180-022-01312-6>. It aims to explain and interpret decision tree ensemble models using a single tree-like structure. 'e2tree' is a new way of explaining an ensemble tree trained through 'randomForest' or 'xgboost' packages.

Version: 0.1.2
Imports: dplyr, doParallel, parallel, foreach, future.apply, ggplot2, Matrix, partitions, purrr, tidyr, randomForest, rpart.plot, Rcpp, RSpectra, ape
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0)
Published: 2025-04-12
Author: Massimo Aria ORCID iD [aut, cre, cph], Agostino Gnasso ORCID iD [aut]
Maintainer: Massimo Aria <aria at unina.it>
BugReports: https://github.com/massimoaria/e2tree/issues
License: MIT + file LICENSE
URL: https://github.com/massimoaria/e2tree
NeedsCompilation: yes
Citation: e2tree citation info
Materials: README NEWS
CRAN checks: e2tree results

Documentation:

Reference manual: e2tree.pdf

Downloads:

Package source: e2tree_0.1.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-devel (arm64): e2tree_0.1.2.tgz, r-release (arm64): e2tree_0.1.2.tgz, r-oldrel (arm64): e2tree_0.1.2.tgz, r-devel (x86_64): e2tree_0.1.2.tgz, r-release (x86_64): e2tree_0.1.2.tgz, r-oldrel (x86_64): e2tree_0.1.2.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=e2tree to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.